Image processing apparatus, X-ray computed tomography apparatus, and image processing method

ABSTRACT

According to one embodiment, an image processing apparatus comprises a storage unit configured to store a plurality of volume data acquired by imaging a predetermined part of an object, the plurality of volume data corresponding to a plurality of phases, a calculation unit configured to calculate a spatial motion vector of each voxel included in each volume data by performing registration between the plurality of volume data, an image generation unit configured to generate an image representing a local motion of the diagnosis part using the motion vector of each voxel, and a display unit configured to display the image representing the local motion of the diagnosis part.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based upon and claims the benefit of priority fromJapanese Patent Application No. 2010-006110, filed Jan. 14, 2010; theentire contents of which are incorporated herein by reference.

FIELD

Embodiments described herein relate generally to an image processingapparatus, an X-ray computed tomography apparatus, and an imageprocessing method.

BACKGROUND

Embodiments described herein relate generally to an image processingapparatus, an X-ray computed tomography apparatus, and an imageprocessing apparatus and, more particularly, to an image processingapparatus, an X-ray computed tomography apparatus, and an imageprocessing method for organ kinetics using medical images, which obtainmotion components between phases from data obtained with time using anX-ray computed tomography apparatus (X-ray CT apparatus), a magneticresonance imaging apparatus (MRI apparatus), or the like and observe theresult.

A method of acquiring, for example, image data of a plurality ofrespiratory phases in the lung field and confirming the tissue kineticsusing an X-ray computed tomography apparatus (X-ray CT apparatus), amagnetic resonance imaging apparatus (MRI apparatus), or the like so asto analyze functions is very effective from the viewpoint of diseasediagnosis and early disease finding. The function analysis result isalso effective from the viewpoint of automated diagnosis (CAD).

The above-described method of grasping kinetics and calculatingquantitative values is practiced in general and has received a greatdeal of attention for a current apparatus such as a CT or MRI capable oftime-serially scanning a wide area.

The conventional result observation methods also include a method ofevaluating a color map, multi planar reconstruction (MPR) image, orthree-dimensional (3D) image as a moving image.

However, the above-described color map is data created based on entiretime information, and information at each timing is lost at the time ofdisplay. A moving image of MPR or 3D image is hard to grasp the motionof each part of the object.

The embodiments have been made in consideration of the above-describedsituation, and has as its object to provide an image processingapparatus, an X-ray computed tomography apparatus, and an imageprocessing method for organ kinetics using medical images, which caneasily grasp the motion of each part.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing the arrangement of an X-ray computedtomography apparatus according to an embodiment;

FIG. 2 is a flowchart for explaining an operation of processing anangiographic image obtained by an X-ray CT apparatus 1 in FIG. 1;

FIG. 3 is a view showing the concept of registration using a referencevolume;

FIGS. 4A, 4B, and 4C are views for explaining a motion vectorcalculation method;

FIGS. 5A and 5B are views showing examples of resultant images;

FIG. 6 is a flowchart illustrating the procedure of motion informationvisualization processing according to the second embodiment;

FIG. 7 is a view showing an example of a vector field image generatedand displayed in step S5 a;

FIG. 8 is a view showing an example of a vector field image generatedand displayed in step S5 a;

FIG. 9 is a flowchart illustrating the procedure of motion informationvisualization processing according to the third embodiment; and

FIG. 10 is a view showing an example of a wire frame image generated anddisplayed in step S5 b.

DETAILED DESCRIPTION

In general, according to one embodiment, an image processing apparatuscomprises a storage unit configured to store a plurality of volume dataacquired by imaging a predetermined part of an object, the plurality ofvolume data corresponding to a plurality of phases, a calculation unitconfigured to calculate a spatial motion vector of each voxel includedin each volume data by performing registration between the plurality ofvolume data, an image generation unit configured to generate an imagerepresenting a local motion of the diagnosis part using the motionvector of each voxel, and a display unit configured to display the imagerepresenting the local motion of the diagnosis part.

The embodiments will now be described with reference to the accompanyingdrawing. Note that an X-ray computed tomography apparatus will beexemplified in the following embodiments. However, the embodiments arenot limited to this example and embodiments related to another medicalimage diagnostic apparatus (for example, magnetic resonance imagingapparatus, ultrasonic diagnostic apparatus, X-ray diagnostic apparatus,or nuclear medicine diagnostic apparatus) or an image processingapparatus using medical images acquired by the medical image diagnosticapparatus can also be implemented.

FIG. 1 is a block diagram showing the arrangement of an X-ray computedtomography apparatus according to an embodiment.

Note that an X-ray computed tomography apparatus 1 uses either therotate-rotate method of integrally rotating the X-ray tube and the X-raydetector about an object or the fix-rotate method of rotating only theX-ray tube about an object while arranging a number of X-ray detectorson a ring. The embodiment is applicable to either method. Apparatusesusing the rotate-rotate method include an apparatus of single-tube typehaving a pair of an X-ray tube and an X-ray detector mounted on a rotaryframe and an apparatus of multi-tube type having a plurality of pairs ofan X-ray tube and an X-ray detector mounted on a rotary frame. Theembodiment is applicable to either type. X-ray detectors include adetector of indirect conversion type which causes a phosphor such as ascintillator to convert X-rays transmitted through an object into lightand then causes a photoelectric conversion element such as a photodiodeto convert the light into electric charges and a detector of directconversion type which uses electron-hole pair generation in asemiconductor by X-rays and their movement to an electrode, that is,photoconduction. The embodiment is applicable to either type.

Referring to FIG. 1, a gantry 10 includes an X-ray tube 11. The X-raytube 11 receives a tube voltage and a filament current from ahigh-voltage generation device via a slip ring mechanism 18, andgenerates cone-beam-shaped X-rays. The X-ray tube 11 is mounted on arotary frame 12 rotatably supported about a rotation axis (Z-axis)together with an X-ray detector 13.

A respiration sensor 17 is provided to detect the respiratory motion ofthe object. In accordance with the inspection target, the respirationsensor 17 can be replaced with an electrocardiograph or heart beatsensor for detecting the phase of the cardiac motion (heart beat) of theobject.

The X-ray detector 13 detects X-rays emitted by the X-ray tube 11 andtransmitted through the object. The X-ray detector 13 is of amulti-slice type or two-dimensional array type corresponding to a conebeam. More specifically, the X-ray detector 13 has a plurality of X-raydetection element arrays juxtaposed along the rotation axis. Each X-raydetection element array has a plurality of X-ray detection elementsarrayed in line along the direction perpendicular to a rotation axis RA.

The output from the X-ray detector 13 is amplified by a data acquisitioncircuit (DAS) 14 for each channel and converted into a digital signal.The signal is sent to a preprocessing device 16 via, for example, anoncontact data transmitting device 15 and undergoes correctionprocessing such as sensitivity correction. The data is stored in aprojection data/image data storage unit 23 as so-called projection datain the stage immediately before reconstruction processing together witha respiratory phase code corresponding to the time the data has beenacquired. A scan controller 20 controls a rotation driving unit, ahigh-voltage generation device 19, the data acquisition circuit 14, theprojection data/image data storage unit 23, and the like for dataacquisition (scan).

A reconstruction unit 24 reconstructs a plurality of two- orthree-dimensional image data in different respiratory phases based onprojection data repetitively acquired by dynamic scan. The plurality oftwo- or three-dimensional image data in different respiratory phases arestored in the projection data/image data storage unit 23 together with arespiratory phase code corresponding to, for example, the center phaseof the projection data set used for the reconstruction processing.

A typical three-dimensional image reconstruction processing method isthe Feldkamp method. As is known, the Feldkamp method is an approximatereconstruction method based on the fan-beam convolution back projectionmethod. Assuming that the cone angle is relatively small, convolutionprocessing is performed by regarding data as fan projection data.However, the back projection processing is performed along an actualray. More specifically, a weight depending on the Z-coordinate isassigned to projection data. The same reconstruction function as in fanbeam reconstruction is convoluted to the weighted projection data. Thedata is then reversely projected along an actual oblique ray having acone angle. The image is reconstructed in accordance with theabove-described procedure.

As described above, the X-ray CT apparatus 1 according to thisembodiment includes an image processing apparatus. The image processingapparatus comprises a specific phase determination unit 25, displayprocessing unit 26, reference point determination unit 27,point-of-interest determination unit 28, vector processing unit 29,pulmonary function index calculation unit 30, and image processing unit31 as well as the projection data/image data storage unit 23.

The specific phase determination unit 25 determines the maximuminspiratory phase and the maximum expiratory phase by specifying, forexample, the maximum and minimum points of the flow-time curve storedtogether with the projection data. The reference point determinationunit 27 sets a reference point at the same anatomical position on theimage of maximum inspiratory phase and the image of maximum expiratoryphase. The reference point determination unit 27 also has a function ofsetting data serving as a reference for registration.

The point-of-interest determination unit 28 sets a plurality of pointsof interest in, for example, the lung field (for example, the pleura,the bronchium, the bronchiole and the other the lung tissues). Apulmonary function index is obtained from, for example, the movingdistance of each point of interest with respect to the reference pointin respiration. The plurality of points of interest are set for each ofthe image of maximum inspiratory phase and the image of maximumexpiratory phase. The plurality of points of interest are set on thelung wall contours, nodes, and tumors. The point-of-interestdetermination unit 28 extracts a lung region from each of the image ofmaximum inspiratory phase and the image of maximum expiratory phase bythreshold processing such as region growing. A point of interest is seton the wall contour of the extracted lung region at each predeterminedangle from the reference point.

The vector processing unit 29 calculates a vector for each of theplurality of points of interest on the image of maximum inspiratoryphase. Similarly, the vector processing unit 29 also calculates a vectorfor each of the plurality of points of interest on the image of maximumexpiratory phase. The vector processing unit 29 also calculates thevector differences between the plurality of vectors concerning theplurality of points of interest on the image of maximum inspiratoryphase and the plurality of vectors concerning the plurality of points ofinterest on the image of maximum expiratory phase for the respectiveangles. That is, the moving distance of each point of interest uponrespiratory motion is quantitatively obtained based on the relativelystationary reference point. The vector processing unit 29 also has afunction of calculating a three-dimensional motion vector ({right arrowover (x)}, {right arrow over (y)}, {right arrow over (z)}) in each voxelbased on the deformation amount in nonlinear registration.

The pulmonary function index calculation unit 30 calculates pulmonaryfunction indices such as the quantitative value of the lung volume ineach phase, the lung volume change rate, and the quantitative value ofeach changed volume from the moving distance of each of the plurality ofpoints of interest in calculated respiratory motion. The displayprocessing unit 26 performs processing necessary for displaying thecalculated pulmonary function indices as numerical values together withimages or in association with a hue or luminance corresponding to eachindex value at a corresponding position of an image, and displays thepulmonary function indices.

The image processing unit 31 processes various kinds of images such as amedical image and a part model. Although not illustrated, the imageprocessing unit 31 is formed from software or hardware (circuit) or bothof them and has a function of registering images and models. The imageprocessing unit 31 also has a function of normalizing the motion vectorcomponents calculated by the vector processing unit 29 and assigningthem to the (R,G,B) colors, and a function of performing nonlinearregistration for data serving as a reference.

An operation of processing an angiographic image will be described nextwith reference to the flowchart of FIG. 2.

An angiographic image obtained using the X-ray CT apparatus 1 shown inFIG. 1 is read out. Note that the readout data has at least two phases.In step S2, a volume serving as a reference for registration is selectedfrom the data read out in step S1. The volume may manually be selectedby the operator. Alternatively, a method of automatically detecting avolume with least motion based on the motion difference between phasesmay be used (FIG. 3). Note that the phase corresponding to the referencevolume will be referred to as a “reference phase” hereinafter.

In step S3, registration processing is performed for each phase based onthe reference volume set in step S2. Registration between the phases isdone using known linear registration or nonlinear registration (forexample, Jpn. Pat. Appln. KOKAI Publication No. 2009-28362, and ShinobuMizuta et al., “Automated, Non-linear Registration Between 3-DimensionalBrain Map and Medical Head Volume”, Medical Imaging Technology vol. 16,No. 3, 1998). Hence, a detailed description of these methods will beomitted.

In step S4, the vector processing unit 29 calculates a motion vectorcomponent ({right arrow over (x)}, {right arrow over (y)}, {right arrowover (z)}) in each voxel based on the deformation amount inregistration. For example, place focus on the moving amount of a voxel35 a ₁ between a voxel 35 ₁ shown in FIG. 4A and a voxel 35 ₂ shown inFIG. 4B after the elapse of a predetermined time. For a moving amount{right arrow over (V_(n))} from the voxel 35 a ₁ to a voxel 35 a ₂, amotion vector component {right arrow over (V_(n))}=({right arrow over(x_(n))},{right arrow over (y_(n))},{right arrow over (z_(n))}) as shownin FIG. 4C is calculated.

In step S5, the motion vector component of each voxel obtained in stepS4 is normalized. The image processing unit 31 assigns the (R,G,B)colors to the three-dimensional x- y-, and z-axes (that is, assignsdifferent colors in accordance with the directions and also assignsluminance values corresponding to the magnitudes of the components). Theassigned image is stored as a new volume For assignment to (R,G,B), theabsolute values (|{right arrow over (x)}|, |{right arrow over (y)}|,|{right arrow over (z)}|) may be calculated, or signed values maydirectly be assigned. For the signed values, the intermediate valuebetween the minimum value and the maximum value of the vector ({rightarrow over (x)}, {right arrow over (y)}, {right arrow over (z)})corresponds to the intermediate value in (R,G,B).

In step S6, the processing operation in steps S3 to S5 described aboveis performed for all volumes, and for other than the last volume, theprocess advances to step S7 to shift to the next volume. The processthen returns to step S3 to perform registration. Volumes in which themotion vector components are converted into RGB are thus generated.

Finally, in step S8, an MPR image is generated using the volumesobtained in steps S3 to S6 described above, and displayed. The image maybe displayed in one phase or as a moving image.

FIGS. 5A and 5B are views showing examples of images processed by theX-ray CT apparatus 1 according to this embodiment. Note that in FIGS. 5Aand 5B, the R component is indicated by ◯, the G component is indicatedby □, and the B component is indicated by Δ for the convenience. Aportion where the components are dense represents that the color of thecomponents is strong (dark). A portion where the components are sparserepresents that the color of the components is weak (light).

For example, when an input image 41 ₂ is combined with a lung referenceimage 41 ₁ shown in FIG. 5A, a resultant image 41 ₃ includes the Rcomponents in a large amount as a whole, as can be seen. That is, sincethe R component corresponds to the x-axis direction, it is determinedbased on the resultant image 41 ₃ that the upper side of the lung mainlymoves in the x-axis direction.

In addition, when an input image 43 ₂ is combined with a lung referenceimage 43 ₁ shown in FIG. 5B, a resultant image 43 ₃ includes the Rcomponents in a large amount as a whole, whereas the B components aredisplayed in a slightly larger amount on the lower right side, as can beseen. That is, it is determined that although the lung moves in thex-axis direction (R component) as a whole, the lower right side moves inthe z-axis direction (B component).

As described above, the motion of a three-dimensional image is assignedto the (R,G,B) colors, and the motion vector components are assigned tothe directions so as to be displayed as the R, G, and B components. Thisallows to easily grasp the motion of each part of the object.

For example, a cancer part hardly moves. For this reason, when the(R,G,B) colors are assigned in the above-described manner, a cancer partis supposedly displayed relatively dark so as to be distinguishable fromother parts.

Second Embodiment

The second embodiment will be described next. In this embodiment, alocal motion of a diagnosis part is indicated as a vector field (vectorfield indication) using arrows at the respective positions.

FIG. 6 is a flowchart illustrating the procedure of motion informationvisualization processing according to the second embodiment. Processingin steps S1 to S4 is the same as that of the first embodiment shown inFIG. 2. Processing in steps S5 a and S6 a will be described below.

Using the calculated motion vector of each voxel in each phase, an imageprocessing unit 31 generates an image representing the local motion of adiagnosis part corresponding to a preselected phase (selected phase).More specifically, the image processing unit 31 sets a predetermined MPRsection on the volume data of the selected phase. Using the calculatedmotion vector of each voxel in the selected phase, the image processingunit 31 generates a vector field image which indicates, by arrows, themoving directions and moving amounts at the respective positions on theMPR section. A display processing unit 26 displays the generated vectorfield image corresponding to the selected phase in a predetermined form(step S5 a).

FIGS. 7 and 8 are views showing examples of the vector field imagegenerated and displayed in step S5 a. As shown in FIGS. 7 and 8, if amotion has occurred during the period from the reference phase to theselected phase at each position of the MPR image, the moving directionis represented by the direction of the arrow, and the moving amount isrepresented by the length of the arrow. If no motion has occurred, noarrow representing the moving direction and moving amount is assigned.Hence, the user can easily grasp the motion of the diagnosis part of theobject at each position by observing the displayed vector field image.

When an instruction to generate the vector field image of another phase(instruction to select another phase) is input, processing in steps S3to S5 a is repetitively executed for each newly selected phase. If noinstruction to select another phase is input, the motion informationvisualization processing ends (step S6 a).

Third Embodiment

The third embodiment will be described next. In this embodiment, a localmotion of a diagnosis part is indicated by a wire frame, surface model,or the like.

FIG. 9 is a flowchart illustrating the procedure of motion informationvisualization processing according to the third embodiment. Processingin steps S1 to S4 is the same as that of the first embodiment shown inFIG. 2. Processing in steps S5 b and S6 b will be described below.

An image processing unit 31 generates a wire frame image representingthe contour of the diagnosis part by a wire frame (or a surface modelimage representing the surface of the diagnosis part) using thereference volume. Similarly, the image processing unit 31 generates awire frame image representing the contour of the diagnosis part by awire frame (or a surface model image representing the surface of thediagnosis part) using a volume corresponding to a preselected phase(selected phase). The image processing unit 31 also generates an imagerepresenting the local motion of the diagnosis part using the generatedwire frame images and the motion vector of each voxel during the periodfrom the reference phase to the selected phase. That is, the imageprocessing unit 31 registers the wire frame corresponding to thereference phase with the wire frame corresponding to the selected phaseand also adds information representing a motion to the wire framecorresponding to the selected phase, thereby generating the imagerepresenting the local motion of the diagnosis part. A displayprocessing unit 26 displays the generated wire frame image correspondingto the selected phase in a predetermined form (step S5 b).

Note that the information representing the motion and to be added to thewire frame corresponding to the selected phase can be of any type. Forexample, (R,G,B) assignment described in the first embodiment may beperformed at each position on the wire frame. Alternatively, vectorfield indication described in the second embodiment may be performed ateach position on the wire frame. Not motion at each position but anaverage motion magnitude and motion direction within a predeterminedrange may be indicated by an arrow or the like.

FIG. 10 is a view showing an example of a wire frame image generated anddisplayed in step S5 b. As shown in FIG. 10, the user can easily andquickly visually recognize the motion at each position the contourduring the period from the reference phase to the selected phase byobserving the wire frame image.

When an instruction to generate the wire frame image of another phase(instruction to select another phase) is input, processing in steps S3to S5 b is repetitively executed for each newly selected phase. If noinstruction to select another phase is input, the motion informationvisualization processing ends (step S6 b).

In the above-described embodiments, one resultant image is displayed foreach part. However, the embodiments are not limited to this. Forexample, the images may be overlaid. In the embodiments, a still imagehas been exemplified. However, the embodiments are not limited to thisand are also applicable to a moving image.

In the embodiments, the reference volume is set in step S2. Registrationwith the reference volume is done to calculate the motion vector of eachvoxel from the phase corresponding to the reference volume. However, theembodiments are not limited to this example. For example, registrationmay be done between chronologically adjacent volumes to calculate themotion vector of each voxel between the phases.

While certain embodiments have been described, these embodiments havebeen presented by way of example only, and are not intended to limit thescope of the inventions. Indeed, the novel embodiments described hereinmay be embodied in a variety of other forms; furthermore, variousomissions, substitutions and changes in the form of the embodimentsdescribed herein may be made without departing from the spirit of theinventions. The accompanying claims and their equivalents are intendedto cover such forms or modifications as would fall within the scope andspirit of the inventions.

What is claimed is:
 1. An image processing apparatus comprising: astorage unit configured to store a plurality of volume data acquired byimaging a predetermined part of an object, the plurality of volume datacorresponding to a plurality of phases; a calculation unit configured tocalculate a motion vector of each voxel included in each volume data byperforming registration between the plurality of volume data; an imagegeneration unit configured to generate an image representing a localmotion of a diagnosis part using the motion vector of each voxel, thelocal motion of the diagnosis part being indicated in a predeterminedset of direction components of the motion vector, one of predetermineddifferent colors and luminances being assigned to a corresponding one ofthe direction components in accordance with a magnitude of thecorresponding one of the direction components; and a display unitconfigured to display the image representing the local motion of thediagnosis part.
 2. The apparatus according to claim 1, wherein thecalculation unit calculates the motion vector by performing registrationbased on predetermined volume data selected from the plurality of volumedata.
 3. The apparatus according to claim 1, wherein the calculationunit calculates the motion vector by performing registration betweenchronologically adjacent volumes.
 4. The apparatus according to claim 1,wherein the calculation unit normalizes the motion vector.
 5. Theapparatus according to claim 1, wherein the image generation unitgenerates the image representing the local motion of the diagnosis partby assigning the components of the motion vector to (R,G,B).
 6. Theapparatus according to claim 1, wherein the image generation unitgenerates the image representing the local motion of the diagnosis partby indicating each motion vector by an arrow at each spatial position.7. The apparatus according to claim 1, wherein the image generation unitgenerates the image representing the local motion of the diagnosis partby visualizing a contour of the predetermined part in a first phase anda contour of the predetermined part in a second phase after elapse of apredetermined time from the first phase.
 8. The apparatus according toclaim 1, wherein the image generation unit generates the imagerepresenting the local motion of the diagnosis part as an MPR image. 9.The image processing apparatus according to claim 1, wherein thepredetermined part of the object includes at least one of a pleura, abronchium and a bronchiole.
 10. An X-ray computed tomography apparatuscomprising: an imaging unit configured to image volume data concerning apredetermined part of an object in a plurality of phases; a calculationunit configured to calculate a spatial motion vector between the phasesfor each voxel included in each volume data by performing registrationbetween the plurality of volume data; an image generation unitconfigured to generate an image representing a local motion of adiagnosis part using the motion vector of each voxel, the local motionof the diagnosis part being indicated in a predetermined set ofdirection components of the motion vector, one of predetermineddifferent colors and luminances being assigned to a corresponding one ofthe direction components in accordance with a magnitude of thecorresponding one of the direction components; and a display unitconfigured to display the image representing the local motion of thediagnosis part.
 11. The apparatus according to claim 10, wherein thecalculation unit calculates the motion vector by performing registrationbased on predetermined volume data selected from the plurality of volumedata.
 12. The apparatus according to claim 10, wherein the calculationunit calculates the motion vector by performing registration betweenchronologically adjacent volumes.
 13. The apparatus according to claim10, wherein the calculation unit normalizes the motion vector.
 14. Theapparatus according to claim 10, wherein the image generation unitgenerates the image representing the local motion of the diagnosis partby assigning the components of the motion vector to (R,G,B).
 15. Theapparatus according to claim 10, wherein the image generation unitgenerates the image representing the local motion of the diagnosis partby indicating each motion vector by an arrow at each spatial position.16. The apparatus according to claim 10, wherein the image generationunit generates the image representing the local motion of the diagnosispart by visualizing a contour of the predetermined part in a first phaseand a contour of the predetermined part in a second phase after elapseof a predetermined time from the first phase.
 17. The apparatusaccording to claim 10, wherein the image generation unit generates theimage representing the local motion of the diagnosis part as an MPRimage.
 18. An image processing method comprising: executing registrationbetween a plurality of volume data acquired by imaging a predeterminedpart of an object using an image processing apparatus, the plurality ofvolume data corresponding to a plurality of phases; calculating aspatial motion vector between the phases for each voxel included in eachvolume data; generating an image representing a local motion of adiagnosis part using the motion vector of each voxel, the local motionof the diagnosis part being indicated in a predetermined set ofdirection components of the motion vector, one of predetermineddifferent colors and luminances being assigned to a corresponding one ofthe direction components in accordance with a magnitude of thecorresponding one of the direction components; and displaying the imagerepresenting the local motion of the diagnosis part.